贝叶斯网络在舰艇导弹防御系统的决策模型优化的应用

Application of Bayesian network in decision model optimization on warship missile defense system

当前,随着全球军事力量的发展,各国在海上作战系统展开了军备竞赛。海军力量的壮大引起了舰艇导弹系统的迅速发展。为了提高海洋军舰的防御能力,需要建立精确的导弹防御系统,对敌方威胁进行评估、并建立相应的决策模型。本文针对舰艇导弹防御系统决策模型对危险识别评估的高精度要求,采用动态贝叶斯网络,使用证据传播算法对贝叶斯网络的节点和传递函数进行分析,进而评估导弹的危险系数,显著提高了舰艇的防御能力。

At present,with the development of global military forces,many nations start militant races in marine Warcraft systems.The strengthening of marine forces cause the missile system targeting at warships.In order to raise the defense capacity of marine warships,precise missile defense systems have to be built in order to estimate on threatens and build corresponding decision models.This paper targets at the high precision requirements of defense system on threaten detection and estimation,applies dynamic Bayesian network,uses evidence broadcasting algorithm to analyze joint and functions,which highs raises the defense capacity of warships.